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Results for “Application characterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Continuous whole-system monitoring toward rapid understanding of production HPC applications and systems

A detailed understanding of HPC applications’ resource needs and their complex interactions with each other and HPC platform resources are critical to achieving scalability and performance. Such understanding has been difficult to achieve because typical application profiling tools do not capture the behaviors of codes under the potentially wide spectrum of actual production conditions and because typical monitoring tools do not capture system resource usage information with high enough fidelity to gain sufficient insight into application performance and demands. In this paper we present both system and application profiling results based on data obtained through synchronized system wide monitoring on a production HPC cluster at Sandia National Laboratories (SNL). We demonstrate analytic and visualization techniques that we are using to characterize application and system resource usage under production conditions for better understanding of application resource needs. Furthermore, our goals are to improve application performance (through understanding application-to-resource mapping and system throughput) and to ensure that future system capabilities match their intended workloads.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

X-ray characterization of the Icarus ultrafast x-ray imager

Ultrafast x-ray imagers developed at Sandia National Laboratories are a transformative diagnostic tool in inertial confinement fusion and high energy density physics experiments. The nanosecond time scales on which these devices operate are a regime with little precedent, and applicable characterization procedures are still developing. This paper presents pulsed x-ray characterization of the Icarus imager under a variety of illumination levels and timing modes. Results are presented for linearity of response, absolute sensitivity, variation of response with gate width, and image quality.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Chemical signature characterization with hyperspectral imagery: novel deep learning model architectures and physically-motivated data augmentation techniques

The high spectral resolution afforded by Hyperspectral Imaging (HSI) sensors is poised to bring unprecedented advancements to signature characterization applications. Thus far, much of the research in the machine learning field devoted to HSI applications has focused on a few specific tasks like land-use land-cover classification. In land classification tasks, spatial information is very important, and model architectures are often designed to leverage spatial contexts. However, it is unclear how well these spatially-tuned models will translate to tasks where spectral information is critical, like the detection and characterization of chemicals. In this work, we compare spectral models (inputs are 1D spectra) and spatial-spectral models (inputs are 3D cubes) in the context of predicting chemical concentration maps. We find that spatial-spectral models perform the best, though we find a wide range in performance across the different architectures tested. Additionally, we find that model performance is impacted by the availability of training data, particularly in scenarios where the training data doesn't fully capture the true variance of real-world conditions. We find that data augmentation can help mitigate sparse coverage of observed parameter space (e.g., seasonal or geographic variability in ground cover), and present augmentation strategies that are tailored to hyperspectral data.

• Artificial intelligence (AI) / machine learning ↗
NASA NTRS1993

Performance analysis of a large-grain dataflow scheduling paradigm

A paradigm for scheduling computations on a network of multiprocessors using large-grain data flow scheduling at run time is described and analyzed. The computations to be scheduled must follow a static flow graph, while the schedule itself will be dynamic (i.e., determined at run time). Many applications characterized by static flow exist, and they include real-time control and digital signal processing. With the advent of computer-aided software engineering (CASE) tools for capturing software designs in dataflow-like structures, macro-dataflow scheduling becomes increasingly attractive, if not necessary. For parallel implementations, using the macro-dataflow method allows the scheduling to be insulated from the application designer and enables the maximum utilization of available resources. Further, by allowing multitasking, processor utilizations can approach 100 percent while they maintain maximum speedup. Extensive simulation studies are performed on 4-, 8-, and 16-processor architectures that reflect the effects of communication delays, scheduling delays, algorithm class, and multitasking on performance and speedup gains.

Young, Steven D.↗
NASA NTRS2010

Development and Application of Wide Bandwidth Magneto-Resistive Sensor Based Eddy Current Probe

The integration of magneto-resistive sensors into eddy current probes can significantly expand the capabilities of conventional eddy current nondestructive evaluation techniques. The room temperature solid-state sensors have typical bandwidths in the megahertz range and resolutions of tens of microgauss. The low frequency sensitivity of magneto-resistive sensors has been capitalized upon in previous research to fabricate very low frequency eddy current sensors for deep flaw detection in multilayer conductors. In this work a modified probe design is presented to expand the capabilities of the device. The new probe design incorporates a dual induction source enabling operation from low frequency deep flaw detection to high frequency high resolution near surface material characterization. Applications of the probe for the detection of localized near surface conductivity anomalies are presented. Finite element modeling of the probe is shown to be in good agreement with experimental measurements.

Wincheski, Russell A.↗
DOE OSTI2021

Quantifying sensitivity in numerical weather prediction-modeled offshore wind speeds through an ensemble modeling approach

A decade of research has shown that numerical weather prediction (NWP)-modeled wind speeds can be highly sensitive to the inputs and setups within the NWP model. For wind resource characterization applications, this sensitivity is often addressed by constructing a range of setups and selecting the one that best validates against observations. However, this approach is not possible in areas that lack high-quality hub height observations, especially offshore wind areas. In such cases, techniques to quantify and disseminate confidence in NWP-modeled wind speeds in the absence of observations are needed. We address this need in the present study and propose best practices for quantifying the spread in NWP-modeled wind speeds. We implement an ensemble approach in which we consider 24 different setups to the Weather Research and Forecasting (WRF) model. We construct the ensemble by considering variations in WRF version, WRF namelist, atmospheric forcing, and sea surface temperature (SST) forcing. Our analysis finds that the standard deviation produces more consistent estimates compared to the interquartile range and tends to be the more conservative estimator for ensemble variability. We further find that model spread increases closer to the surface and on shorter time scales. In conclusion, we explore methods to attribute total ensemble variability to the different ensemble components (e.g., atmospheric forcing and SST product) and find that contributions by components also vary depending on time scale. We anticipate that the methods and results presented in this paper will provide a reasonable foundation for further research into ensemble-based wind resource data sets.

17 WIND ENERGY↗
DOE OSTI2018

Fractal nature structure reconstruction method in designing microstructure properties

Highlights: • Structure and material’s properties, within the material’s consolidation triad: Synthesis – Structure – Properties. • The grain prediction methods is based on the measurements of the solid Euclidean geometric fractal characteristics. • The intergranular contacts inside the BaTiO3 -ceramic are responsible for intergranular capacities. • The inner complex geometry of intergrain contacts imposes fractal correction factor for permeability. - Abstract: In the process of predicting materials properties, it is necessary to predict microstructures. This is important for ceramic materials, for the purpose of miniaturization and for a higher level of integration. Although the method of material structure reconstruction is for the first time used on BaTiO{sub 3}-ceramics by these authors, it can also be used for silicate, refractory and other ceramics, and, for any powder-based material. The reconstruction is based on the grain perimeter fractal analysis and the Richardson method. The main contribution of this paper is establishing the relationship between the electronic properties of BaTiO{sub 3}-ceramics and its microstructural fractal nature. Similar relations can be used for any ceramics or even any materials. The samples consolidation includes both powder pressing (cold sintering phase) and sintering in a furnace (hot sintering phase). The fractal nature characterization has a very important role from the powder phase up to the final microstructure, through which structures it directly impacts electro-physical and other ceramics properties. Thereby, the new possibilities in the microstructure characterization applications are directly introduced to an engineering system, providing the new solutions related to computer aided support. This creates new industrial production and application possibilities, especially in the process of ceramics material consolidation, now based on microstructural properties, which is providing a basis for “fractal electronics’’ development.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Low dimensional metal halide perovskites and hybrids

Organic-inorganic metal halide hybrids are an important class of crystalline materials with exceptional structural and property tunability. Recently metal halide perovskites with ABX 3 structure have been extensively investigated as new generation semiconductors for various optoelectronic devices, including photovoltaic cells, light emitting diodes, photodetectors, and lasers, for their exceptional optical and electronic properties. By controlling the morphological dimensionality, low dimensional metal halide perovskites, including 2D perovskite nanoplatelets, 1D perovskite nanowires, and 0D perovskite quantum dots, have been developed to exhibit distinct properties from their bulk counterparts, due to quantum size effects. Besides ABX 3 perovskites, organic-inorganic metal halide hybrids, containing the same fundamental building block of metal halide octahedra (BX 6 ), can also be assembled to possess other types of crystallographic structures. Using appropriate organic and inorganic components, low dimensional organic-inorganic metal halide hybrids with 2D, quasi-2D, corrugated-2D, 1D, and 0D structures at the molecular level have been developed and studied. Due to the strong quantum confinement and site isolation, these low dimensional metal halide hybrids at the molecular level exhibit remarkable and unique properties that are significantly different from those of ABX 3 perovskites. In light of the rapid development of low dimensional metal halide perovskites and hybrids, it is indeed timely to review the recent progress in these areas. Also, there is a need to clarify the difference between morphological low dimensional metal halide perovskites and molecular level low dimensional metal halide hybrids, as currently the terminologies of low dimensional perovskites are not appropriately used in many cases. Finally, in this review article, we discuss the synthesis, characterization, application, and computational studies of low dimensional metal halide perovskites and hybrids.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Probing interfacial energetics and charge transfer kinetics in semiconductor nanocomposites: New insights into heterostructured TiO 2 /BiVO 4 photoanodes

Heterostructured nanocomposites offer promise for creating systems exhibiting functional properties that exceed those of the isolated components. For solar energy conversion, such combinations of semiconducting nanomaterials can be used to direct charge transfer along pathways that reduce recombination and promote efficient charge extraction. However, interfacial energetics and associated kinetic pathways often differ significantly from predictions derived from the characteristics of pure component materials, particularly at the nanoscale. Here, the emergent properties of TiO 2 /BiVO 4 nanocomposite photoanodes are explored using a combination of X-ray and optical spectroscopies, together with photoelectrochemical (PEC) characterization. Application of these methods to both the pure components and the fully assembled nanocomposites reveals unpredicted interfacial energetic alignment, which promotes ultrafast injection of electrons from BiVO 4 into TiO 2 . Physical charge separation yields extremely long-lived photoexcited states and correspondingly enhanced photoelectrochemical functionality. This work highlights the importance of probing emergent interfacial energetic alignment and kinetic processes for understanding mechanisms of solar energy conversion in complex nanocomposites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Small-angle scattering interferometry with neutron orbital angular momentum states

Methods to prepare and characterize neutron helical waves carrying orbital angular momentum (OAM) were recently demonstrated at small-angle neutron scattering (SANS) facilities. These methods enable access to the neutron orbital degree of freedom which provides new avenues of exploration in fundamental science experiments as well as in material characterization applications. However, it remains a challenge to recover phase profiles from SANS measurements. We introduce and demonstrate a novel neutron interferometry technique for extracting phase information that is typically lost in SANS measurements. An array of reference beams, with complementary structured phase profiles, are put into a coherent superposition with the array of object beams, thereby manifesting the phase information in the far-field intensity profile. We demonstrate this by resolving petal-structure signatures of helical wave interference for the first time: an implementation of the long-sought recovery of phase information from small-angle scattering measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-fidelity parallel entangling gates on a neutral-atom quantum computer

The ability to perform entangling quantum operations with low error rates in a scalable fashion is a central element of useful quantum information processing. Neutral-atom arrays have recently emerged as a promising quantum computing platform, featuring coherent control over hundreds of qubits and any-to-any gate connectivity in a flexible, dynamically reconfigurable architecture. The main outstanding challenge has been to reduce errors in entangling operations mediated through Rydberg interactions. Here we report the realization of two-qubit entangling gates with 99.5% fidelity on up to 60 atoms in parallel, surpassing the surface-code threshold for error correction. Our method uses fast, single-pulse gates based on optimal control, atomic dark states to reduce scattering and improvements to Rydberg excitation and atom cooling. We benchmark fidelity using several methods based on repeated gate applications, characterize the physical error sources and outline future improvements. Finally, we generalize our method to design entangling gates involving a higher number of qubits, which we demonstrate by realizing low-error three-qubit gates. By enabling high-fidelity operation in a scalable, highly connected system, these advances lay the groundwork for large-scale implementation of quantum algorithms, error-corrected circuits and digital simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

INR-TEM: Robust cavity detection in multifocus TEM images via implicit neural representations

When characterizing materials using transmission electron microscopy (TEM) images, detecting and quantifying small features in microstructures, such as cavities, pose significant challenges. Off-the-shelf object detection models, including YOLOv8, show considerable performance degradation, particularly when images vary in resolution and the objects of interest possess a low percentage of the total image region of interest. In this study, we introduce a novel detection pipeline that incorporates an implicit neural representation (INR)-based detection method, INR-TEM, and two-modality imaging (e.g., under-focused and over-focused images typically acquired during materials characterization) to improve object detection performance. The INR-TEM method incorporates a pixel-wise prediction principle inspired by pixel-wise centerness weighting. INR-TEM demonstrates superior robustness to resolution variability, maintaining high detection accuracy even at low image resolutions compared to YOLOv8. To leverage INR-TEM effectively in real-world two-modality characterization applications, we further integrate a two-stage motion correction pipeline designed explicitly for aligning multifocus TEM images. The alignment process, comprising keypoint (based on scale-invariant feature transform, SIFT) and intensity matching, significantly mitigates the adverse effects of perceived motion-induced image degradation during through-focal TEM imaging, directly enhancing INR-TEM’s detection capability over conventional single-focus images. Our integrated INR-TEM cavity detection framework notably improves performance across various cavity sizes, outperforming off-the-shelf YOLOv8 detections that rely on a single image modality.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The 2020 photovoltaic technologies roadmap

Over the past decade, the global cumulative installed photovoltaic (PV) capacity has grown exponentially, reaching 591 GW in 2019. Rapid progress was driven in large part by improvements in solar cell and module efficiencies, reduction in manufacturing costs and the realization of levelized costs of electricity that are now generally less than other energy sources and approaching similar costs with storage included. Given this success, it is a particularly fitting time to assess the state of the photovoltaics field and the technology milestones that must be achieved to maximize future impact and forward momentum. This roadmap outlines the critical areas of development in all of the major PV conversion technologies, advances needed to enable terawatt-scale PV installation, and cross-cutting topics on reliability, characterization, and applications. Each perspective provides a status update, summarizes the limiting immediate and long-term technical challenges and highlights breakthroughs that are needed to address them. In total, this roadmap is intended to guide researchers, funding agencies and industry in identifying the areas of development that will have the most impact on PV technology in the upcoming years.

14 SOLAR ENERGY↗
DOE OSTI2020

Laser Cutting and Micromachining for Localized and Targeted Solar Cell Characterization

Laser cutting and micromachining can be applied to solar cell materials for processing and characterization applications. An ultrashort pulse (USP) laser with sub-picosecond pulse width can remove material with minimal thermal effects or damage, which is termed `cold ablation'. Such USP laser cutting and scribing can be implemented for isolating areas within a larger cell while maintaining electrical performance and preventing laser-induced damage and shunting. Laser micromachining has been used to isolate a shunt to improve cell performance and to isolate a small, selected area to define a sample suitable for deep level transient spectroscopy.

14 SOLAR ENERGY↗
DOE OSTI2025

Spatio-spectral quantum state estimation of photon pairs from optical fiber using stimulated emission

Developing a quantum light source that carries more than one bit per photon is pivotal for expanding quantum information applications. Characterizing a high-dimensional multiple-degree-of-freedom source at the single-photon level is challenging due to the large parameter space as well as limited emission rates and detection efficiencies. Here, we characterize photon pairs generated in optical fiber in the transverse-mode and frequency degrees of freedom by applying stimulated emission in both degrees of freedom while detecting in one of them at a time. This method may be useful in the quantum state estimation and optimization of various photon-pair source platforms in which complicated correlations across multiple degrees of freedom may be present.

Kim, Dong Beom (ORCID:0000000346887375)↗
DOE OSTI2017

Assessment of Laser-Driven Pulsed Neutron Sources for Poolside Neutron-based Advanced NDE – A Pathway to LANSCE-like Characterization at INL

A variety of opportunities for characterization of fresh nuclear fuels using thermal (~25meV) and epithermal (~10eV) neutrons have been documented at Los Alamos National Laboratory. They include spatially resolved non-destructive characterization of features, isotopic enrichment, chemical heterogeneity and stoichiometry. The LANSCE spallation neutron source is well suited in neutron fluence and temporal characteristics for studies of fuels. However, recent advances in high power short pulse lasers suggest that compact neutron sources might, over the next decade, become viable at a price point that would permit their consideration for poolside characterization on site at irradiation facilities. In a laser-driven neutron source the laser is used to accelerate deuterium ions into a beryllium target where neutrons are produced. At this time, the technology is new and their total neutron production is approximately four orders of magnitude less than a facility like LANSCE. However, recent measurements on a sub-optimized system demonstrated >10 10 neutrons in sub-nanosecond pulses in predominantly forward direction. The compactness of the target system compared to a spallation target may allow exchanging the target during a measurement to e.g. characterize a highly radioactive sample with thermal, epithermal, and fast neutrons as well as hard X-rays, thus avoiding sample handling. At this time several groups are working on laser-driven neutron production and are advancing concepts for lasers, laser targets, and optimized neutron target/moderator systems. Advances in performance sufficient to enable poolside fuels characterization with LANSCE-like fluence on sample within a decade may be possible. This report describes the underlying physics and state-of-the-art of the laser-driven neutron production process from the perspective of the DOE/NE mission. It also discusses the development and understanding that will be necessary to provide customized capability for characterization of irradiated fuels. Potential operational advantages compared to a spallation neutron source include reduced shielding complexity, reduced energy requirements, and a production target free of fission products. Contributors to this report include experts in laser-driven neutron production (Roth, Fernandez), laser design (Haefner, Siders, Leemans), laser target design (Glenzer), spallation target/moderator design (Mocko), neutron instrumentation and characterization applications (Vogel, Bourke).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

LEED: A Lightwave Energy-Efficient Datacenter

The Lightwave Energy-Efficient Datacenter (LEED) program is a disruptive “green-field” approach that provides a quantum leap in the energy efficiency of datacenters. LEED’s fundamental value proposition is that a novel and re-architected optical network—RotorNet— can deliver “more bandwidth per buck” as well as unique system-level attributes that significantly improve overall datacenter energy efficiency and performance. LEED has developed three system-level testbeds. The first testbed uses calibrated hardware and software power measurements to determine server energy efficiency as a function of network bandwidth and workload. These measurements have shown that increasing network communications bandwidth dramatically increases server energy efficiency providing a realistic path to the overall ENLITENED program goal of doubling the number of transactions per joule. The second testbed demonstrates key hardware: a prototype low-loss, high-port count optical “selector switch”. This switch was fabricated, racked, and tested. Measured switch characteristics include loss, bandwidth, crosstalk, switch time, system-level switch time (including the transceivers), and bit error rate. The third testbed demonstrates a fully working and manufactured pinwheel design which dramatically lowers the cost of design, while delivering high switch radix and low reconfiguration times. The LEED project has tied these three novel photonic switch prototypes together with production servers and software through the development of a novel FPGA-based NIC platform called Corundum. Corundum ensures that the packet-switched protocols supported by commodity operating systems and devices can interface with the Rotor switch design. The LEED group has used this combined hardware and software prototype to characterize applications running at a commercially relevant scale. The project has used a combination of enhanced optical modulation amplitude (OMA) modulators, broadband multiplexers and demultiplexers, avalanche photodiodes, and a novel burst-mode receivers to enable the insertion of LEED-developed optical switches without the need for expensive optical amplification. Our modeling has shown that measured LEED-developed device characteristics can achieve link characteristics of 2 pJ/bit including both transceivers and the Rotor switch. In summary, the LEED program has demonstrated a credible and practical path, through novel hardware and software, to realize the program objectives of ENLITENED. The net result will ensure that the United States maintains its strength in the crucial sector of Information Technology, which is vital to both our economic security and our national security.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗